Zicheng Su is a Distinguished Research Fellow/Associate Professor and PhD supervisor at the College of Transportation, Tongji University. He received his B.Eng. from Sun Yat-sen University (2018) and his PhD in Systems Engineering from City University of Hong Kong (2022), followed by postdoctoral research at the same institution (2022–2023). His research focuses on active traffic control and mobility services for large-scale urban networks, leveraging large language models (LLMs), reinforcement learning, and other AI technologies to enhance the resilience, efficiency, and travel experience of transportation systems. He has published over 30 papers in leading transportation journals including Transportation Research Part A/B/C and IEEE Transactions on Intelligent Transportation Systems, with 16 papers as first or corresponding author. His work has been selected for presentation at ISTTT (biennial, acceptance rate ~10%, podium presentation) and CCF-A conferences AAAI (twice as oral presentation) and ICLR. He has received 2 national-level first-class science and technology awards and 3 best paper awards at international conferences. He has served as principal investigator of an NSFC grant, received the CCF-DiDi GAIA Young Scholar Fund for three consecutive years, and participated in multiple national and provincial key research projects. He has been seconded to the Ministry of Transport (MoT) of China, and currently serves as Chair of the Road Network Traffic Control Committee at the World Transport Convention (WTC). In close collaboration with DiDi, Alipay, Streamax Technology, and other leading industry partners, his algorithms for ride-hailing subsidy allocation and vehicle rebalancing have been successfully deployed on the DiDi platform.
Educational background
Sep. 2014 – Jun. 2018, Sun Yat-sen University, B.Eng. in Transportation Engineering
Sep. 2018 – Oct. 2022, City University of Hong Kong, Ph.D. in Systems Engineering
Work experience
Oct. 2022 – Jul. 2023, City University of Hong Kong, Postdoctoral Fellow (Systems Engineering)
Sep. 2023 – Sep. 2024, College of Transportation Engineering, Tongji University,Distinguished Research Fellow
Sep. 2024 – Mar. 2026, College of Transportation, Tongji University,Distinguished Research Fellow
Apr. 2026 – Present, College of Transportation, Tongji University,Distinguished Research Fellow/Associate Professor
Research interests
Network Traffic Flow Modeling; Traffic Control; Mobility and ride-hailing; Reinforcement Learning and Large Language Models for Transportation
Honors & Awards
1.First Prize in Science and Technology, China Highway Construction Industry Association, 2025
2.First Prize in Science and Technology, China Communications and Transportation Association, 2024
3.Shanghai Leading Talent (Overseas), 2023
4.Honourable Mention, HKSTS Outstanding Dissertation Award – Gordon Newell Memorial Prize, 2023
5. Winner, HKSTS Outstanding Student Paper Award, 2021,
Representative Publications
(Full list: https://scholar.google.co.jp/citations?user=-uhcC6EAAAAJ&hl=en&oi=sra)
1. Traffic control for large-scale urban networks
(1)Su, Z., Chow, A.H.F., Fang, C., Liang, E., & Zhong, R. (2023). Hierarchical control for stochastic network traffic with reinforcement learning.Transportation Research Part B, 167, 196-216. (Bi-level optimization)
(2)Su, Z., Chow, A.H.F., & Zhong, R. (2021). Adaptive network traffic control with an integrated model-based and data-driven approach and a decentralised solution method.Transportation Research Part C, 128, 103154. (Signal control;ISTTT podium presentation)
(3)Su, Z., Chow, A.H.F., Zheng, N., Huang, Y., Liang, E., & Zhong, R. (2020). Neuro-dynamic programming for optimal control of macroscopic fundamental diagram systems.Transportation Research Part C, 116, 102628. (Perimeter control)
2.Mobility and Travel Experience
(1)Guo, Y.,Su, Z.*, Yang, H., Liang, E., Zhong, C., & Ma, W. (2026). A smart predict-then-optimize framework for vehicle rebalancing problem.Transportation Research Part B, 206, 103411. (Vehicle rebalancing;deployed on DiDi platform)
(2)Yang, J., Chen, L.,Su, Z.*, Ma, W., Zou, Z., & An, K. (2025). Decision-focused learning for optimal subsidy allocation in ride-hailing services.Transportation Research Part C, 180, 105301. (Subsidy allocation;deployed on DiDi platform)
(3)Li, M., Fan, C., Yan, H., Wu, P.,Su, Z.*, & Ma, W. (2026). Urban traffic evaluation with social media data: A consensus-based LLM negotiation paradigm.Transportation Research Part A, 208, 104980. (LLM-based traffic evaluation; mentoredundergraduate as first author)
(4)Gao, S., Ran, Q.,Su, Z.*, Wang, L., Ma, W., & Hao, R. (2024). Evaluation system for urban traffic intelligence based on travel experiences: A sentiment analysis approach.Transportation Research Part A, 187, 104170. (Sentiment-based experience evaluation;undergraduate thesisoutcome)
3.Artificial Intelligence and Machine Learning Theory
(1)Yang, J.,Su, Z.*, Zou, Z., Zhen, P., Ma, W., & An, K. (2026). Optimal treatment assignment from observational data: A decision-focused learning approach via pseudo labels. In ICLR 2026 Workshop on AI for Mechanism Design and Strategic Decision Making. (CCF-A; causal inference)
(2)Yang, J., Liang, E.,Su, Z.*, Zou, Z., Zhen, P., Guo, J., ... & An, K. (2025). DFF: decision-focused fine-tuning for smarter predict-then-optimize with limited data. In AAAI 2025 (oral), Vol. 39, No. 25, pp. 26868-26876. (CCF-A; decision-focused learning)
(3)Liang, E.,Su, Z., Fang, C., & Zhong, R. (2022). OAM: An option-action reinforcement learning framework for universal multi-intersection control. In AAAI 2022 (oral), Vol. 36, No. 4, pp. 4550-4558. (CCF-A; generalizable reinforcement learning)